Feats: A database of semantic features for early produced noun concepts.

Semantic feature production norms have several desirable characteristics that have supported models of representation and processing in adults. However, several key challenges have limited the use of semantic feature norms in studies of early language acquisition. First, existing norms provide uneven and inconsistent coverage of early-acquired concepts that are typically produced and assessed in children under the age of three, which is a time of tremendous growth of early vocabulary skills. Second, it is difficult to assess the degree to which young children may be familiar with normed features derived from these adult-generated datasets. Third, it has been difficult to adopt standard methods to generate semantic network models of early noun learning. Here, we introduce Feats-a tool that was designed to make headway on these challenges by providing a database, the Language Learning and Meaning Acquisition (LLaMA) lab Noun Norms that extends a widely used set of feature norms McRae et al. Behavior Research Methods 37, 547-559, (2005) to include full coverage of noun concepts on a commonly used early vocabulary assessment. Feats includes several tools to facilitate exploration of features comprising early-acquired nouns, assess the developmental appropriateness of individual features using toddler-accessibility norms, and extract semantic network statistics for individual vocabulary profiles. We provide a tutorial overview of Feats. We additionally validate our approach by presenting an analysis of an overlapping set of concepts collected across prior and new data collection methods. Furthermore, using network graph analyses, we show that the extended set of norms provides novel, reliable results given their enhanced coverage.

Thematic and other semantic relations central to abstract (and concrete) concepts.

In this article, we discuss multiple types of meaningful (semantic) relations underlying abstract (as compared to concrete) concepts. We adopt the viewpoint that words act as cues to meaning (Elman in Ment Lexicon 6(1):1-34, 2011; Lupyan and Lewis in Lang Cogn Neurosci 34(10):1319-1337, 2019), which is dependent on the dynamic contents of a comprehender's mental model of the situation. This view foregrounds the importance of both linguistic and real-world context as individuals make sense of words, flexibly access relevant knowledge, and understand described events and situations. We discuss theories of, and experimental work on, abstract concepts through the lens of the importance of thematic and other semantic relations. We then tie these findings to the sentence processing literature in which such meaningful relations within sentential contexts are often experimentally manipulated. In this literature, some specific classes/types of abstract words have been studied, although not comprehensively, and with limited connection to the literature on knowledge underlying abstract concepts reviewed herein. We conclude by arguing that the ways in which humans understand relatively more abstract concepts, in particular, can be informed by the careful study of words presented not in isolation, but rather in situational and linguistic contexts, and as a function of individual differences in knowledge, goals, and beliefs.

Universal Features in Phonological Neighbor Networks.

Human speech perception involves transforming a countinuous acoustic signal into discrete linguistically meaningful units (phonemes) while simultaneously causing a listener to activate words that are similar to the spoken utterance and to each other. The Neighborhood Activation Model posits that phonological neighbors (two forms [words] that differ by one phoneme) compete significantly for recognition as a spoken word is heard. This definition of phonological similarity can be extended to an entire corpus of forms to produce a phonological neighbor network (PNN). We study PNNs for five languages: English, Spanish, French, Dutch, and German. Consistent with previous work, we find that the PNNs share a consistent set of topological features. Using an approach that generates random lexicons with increasing levels of phonological realism, we show that even random forms with minimal relationship to any real language, combined with only the empirical distribution of language-specific phonological form lengths, are sufficient to produce the topological properties observed in the real language PNNs. The resulting pseudo-PNNs are insensitive to the level of lingustic realism in the random lexicons but quite sensitive to the shape of the form length distribution. We therefore conclude that "universal" features seen across multiple languages are really string universals, not language universals, and arise primarily due to limitations in the kinds of networks generated by the one-step neighbor definition. Taken together, our results indicate that caution is warranted when linking the dynamics of human spoken word recognition to the topological properties of PNNs, and that the investigation of alternative similarity metrics for phonological forms should be a priority.

Thematic relatedness production norms for 100 object concepts.

Knowledge of thematic relations is an area of increased interest in semantic memory research because it is crucial to many cognitive processes. One methodological issue that researchers face is how to identify pairs of thematically related concepts that are well-established in semantic memory for most people. In this article, we review existing methods of assessing thematic relatedness and provide thematic relatedness production norming data for 100 object concepts. In addition, 1,174 related concept pairs obtained from the production norms were classified as reflecting one of the five subtypes of relations: attributive, argument, coordinate, locative, and temporal. The database and methodology will be useful for researchers interested in the effects of thematic knowledge on language processing, analogical reasoning, similarity judgments, and memory. These data will also benefit researchers interested in investigating potential processing differences among the five types of semantic relations.

Using network science to provide insights into the structure of event knowledge.

The structure of event knowledge plays a critical role in prediction, reconstruction of memory for personal events, construction of possible future events, action, language usage, and social interactions. Despite numerous theoretical proposals such as scripts, schemas, and stories, the highly variable and rich nature of events and event knowledge have been formidable barriers to characterizing the structure of event knowledge in memory. We used network science to provide insights into the temporal structure of common events. Based on participants' production and ordering of the activities that make up events, we established empirical profiles for 80 common events to characterize the temporal structure of activities. We used the event networks to investigate multiple issues regarding the variability in the richness and complexity of people's knowledge of common events, including: the temporal structure of events; event prototypes that might emerge from learning across many experiential instances and be expressed by people; the degree to which scenes (communities) are present in various events; the degree to which people believe certain activities are central to an event; how centrality might be distributed across an event's activities; and similarities among events in terms of their content and their temporal structure. Thus, we provide novel insights into human event knowledge, and describe 18 predictions for future human studies.

What we mean when we say semantic: Toward a multidisciplinary semantic glossary.

Tulving characterized semantic memory as a vast repository of meaning that underlies language and many other cognitive processes. This perspective on lexical and conceptual knowledge galvanized a new era of research undertaken by numerous fields, each with their own idiosyncratic methods and terminology. For example, "concept" has different meanings in philosophy, linguistics, and psychology. As such, many fundamental constructs used to delineate semantic theories remain underspecified and/or opaque. Weak construct specificity is among the leading causes of the replication crisis now facing psychology and related fields. Term ambiguity hinders cross-disciplinary communication, falsifiability, and incremental theory-building. Numerous cognitive subdisciplines (e.g., vision, affective neuroscience) have recently addressed these limitations via the development of consensus-based guidelines and definitions. The project to follow represents our effort to produce a multidisciplinary semantic glossary consisting of succinct definitions, background, principled dissenting views, ratings of agreement, and subjective confidence for 17 target constructs (e.g., abstractness, abstraction, concreteness, concept, embodied cognition, event semantics, lexical-semantic, modality, representation, semantic control, semantic feature, simulation, semantic distance, semantic dimension). We discuss potential benefits and pitfalls (e.g., implicit bias, prescriptiveness) of these efforts to specify a common nomenclature that other researchers might index in specifying their own theoretical perspectives (e.g., They said X, but I mean Y).

Perirhinal cortex automatically tracks multiple types of familiarity regardless of task-relevance.

Perirhinal cortex (PrC) has long been implicated in familiarity assessment for objects and corresponding concepts. However, extant studies have focused mainly on changes in familiarity induced by recent exposure in laboratory settings. There is an increasing appreciation of other types of familiarity signals, in particular graded familiarity accumulated throughout one's lifetime. In prior work (Duke et al., 2017, Cortex, 89, 61-70), PrC has been shown to track lifetime familiarity ratings when participants make related judgements. A theoretically important characteristic of familiarity is its proposed automaticity. Support for automaticity comes from a documented impact of recent stimulus exposure on behavioral performance, and on PrC signals, under conditions in which this exposure is not task relevant. In the current fMRI study, we tested whether PrC also tracks lifetime familiarity of object concepts automatically, and whether this type of familiarity influences behavior even when it is not task relevant. During scanning, neurotypical participants (N = 30, age range 18-40, 7 males) provided animacy judgements about concrete object concepts presented at differing frequencies in an initial study phase. In a subsequent test phase, they made graded judgements of recent or lifetime familiarity. Behavioral performance showed sensitivity to lifetime familiarity even when it was not relevant for the task at hand. Across five sets of fMRI analyses, we found that PrC consistently tracked recent and lifetime familiarity of object concepts regardless of the task performed. Critically, while several other temporal-lobe regions also showed isolated familiarity effects, none of them tracked familiarity with the same consistency. These findings demonstrate that PrC automatically tracks multiple types of familiarity. They support models that assign a broad role in the representation of information about object concepts to this structure.

Predictive language comprehension in Parkinson's disease.

Verb and action knowledge deficits are reported in persons with Parkinson's disease (PD), even in the absence of dementia or mild cognitive impairment. However, the impact of these deficits on combinatorial semantic processing is less well understood. Following on previous verb and action knowledge findings, we tested the hypothesis that PD impairs the ability to integrate event-based thematic fit information during online sentence processing. Specifically, we anticipated persons with PD with age-typical cognitive abilities would perform more poorly than healthy controls during a visual world paradigm task requiring participants to predict a target object constrained by the thematic fit of the agent-verb combination. Twenty-four PD and 24 healthy age-matched participants completed comprehensive neuropsychological assessments. We recorded participants' eye movements as they heard predictive sentences (The fisherman rocks the boat) alongside target, agent-related, verb-related, and unrelated images. We tested effects of group (PD/control) on gaze using growth curve models. There were no significant differences between PD and control participants, suggesting that PD participants successfully and rapidly use combinatory thematic fit information to predict upcoming language. Baseline sentences with no predictive information (e.g., Look at the drum) confirmed that groups showed equivalent sentence processing and eye movement patterns. Additionally, we conducted an exploratory analysis contrasting PD and controls' performance on low-motion-content versus high-motion-content verbs. This analysis revealed fewer predictive fixations in high-motion sentences only for healthy older adults. PD participants may adapt to their disease by relying on spared, non-action-simulation-based language processing mechanisms, although this conclusion is speculative, as the analyses of high- vs. low-motion items was highly limited by the study design. These findings provide novel evidence that individuals with PD match healthy adults in their ability to use verb meaning to predict upcoming nouns despite previous findings of verb semantic impairment in PD across a variety of tasks.

Investigating the Extent to which Distributional Semantic Models Capture a Broad Range of Semantic Relations.

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract-concrete continuum (19 sets of ratings). We found that, overall, the DSMs are best at capturing overall semantic similarity and also can capture verb-noun thematic role relations and noun-noun event-based relations that play important roles in sentence comprehension. Interestingly, Skip-gram and CBOW performed the best in terms of capturing similarity, whereas GloVe dominated the thematic role and event-based relations. We discuss the theoretical and practical implications of our results, make recommendations for users of these models, and demonstrate significant differences in model performance on event-based relations.

Can you touch the N400? The interactive effects of body-object interaction and task demands on N400 amplitudes and decision latencies.

The effects of semantic richness on N400 amplitudes remain unclear. Some studies have reported semantic richness evoking greater N400s, whereas others have reported the opposite effect. Moreover, N400 effects of some semantic richness variables, such as body-object interaction (BOI), have yet to be demonstrated. BOI quantifies the degree to which a word's referent is easy to interact with; words such as bicycle are high-BOI whereas words such as butterfly are low-BOI. We examined BOI effects on N400 amplitudes and decision latencies in two semantic tasks. We found that in a touchable/untouchable task, low-BOI words (e.g., butterfly) evoked greater N400s than high-BOI words (e.g., bicycle), but there was no difference in decision latencies. Conversely, in a concrete/abstract task, high and low-BOI words evoked similar N400s, but decision latencies were shorter for high-BOI than for low-BOI words. Our results show that semantic richness upstream and downstream effects are dissociable and task dependent.

Wrong or right? Brain potentials reveal hemispheric asymmetries to semantic relations during word-by-word sentence reading as a function of (fictional) knowledge.

How does individual-level variation in experience and knowledge influence neural mechanisms important for real-time language comprehension? We used event-related brain potentials (ERPs) combined with lateralized visual field (VF) presentation of sentence-final words to examine asymmetries in hemispheric processing as individuals who varied in their knowledge of the fictional world of Harry Potter (HP) read sentences about general topics and HP. HP sentence endings were either contextually supported, unrelated anomalies, or semantically related anomalies. Amongst HP experts, we observed contextual support effects with presentation to both left and right VFs, but related anomaly effects only with presentation to the left VF (right hemisphere). Our findings are in line with accounts in which the left hemisphere (LH) activates relatively narrow/specific semantic information and the RH activates a broader range of semantic relations, including those relating to the construction of mental/situation models, as individuals attempt to comprehend sentences, one word at a time. We suggest that RH-biased hemispheric asymmetries in processing related (but linguistically inappropriate) words in written sentences may emerge as a function of each individual's degree of relevant knowledge. We tentatively hypothesize that content experts may optimize hemispheric differences in scope of semantic activation to maximize both precision (in the LH) and flexibility (in the RH) during language comprehension.

Knowledge of the temporal structure of events in relation to autistic traits and social ability.

Event knowledge, a person's understanding of patterns of activities in the world, is crucial for everyday social interactions. Social communication differences are prominent in autism, which may be related to atypical event knowledge, such as atypical knowledge of the sequences of activities that comprise the temporal structure of events. Previous research has found that autistic individuals have atypical event knowledge, but research in this area is minimal, particularly regarding autistic individuals' knowledge of the temporal structure of events. Furthermore, no studies have investigated the link between event knowledge and autistic traits in a non-clinical sample. We investigated relationships between event knowledge and autistic traits in individuals from the general population with varying degrees of autistic traits. We predicted that atypical ordering of event activities is related to autistic traits, particularly social communication abilities, but not other clinical traits. In Study 1, atypical ordering of event activities correlated with social ability, but not with most measures of repetitive behaviours and restricted interests. In Study 2, the typicality of activity ordering varied by participants' social ability and the social nature of the events. Relationships were not found between event activity ordering and other clinical traits. These findings suggest a relationship between autistic traits, specifically social abilities, and knowledge of the temporal structure of events in a general population sample.

An electrophysiological study of task demands on concreteness effects: evidence for dual coding theory.

We examined ERP responses during the generation of word associates or mental images in response to concrete and abstract concepts. Of interest were the predictions of dual coding theory (DCT), which proposes that processing lexical concepts depends on functionally independent but interconnected verbal and nonverbal systems. ERP responses were time-locked to either stimulus onset or response to compensate for potential latency differences across conditions. During word associate generation, but not mental imagery, concrete items elicited a greater N400 than abstract items. A concreteness effect emerged at a later time point during the mental imagery task. Data were also analyzed using time-frequency analysis that investigated synchronization of neuronal populations over time during processing. Concrete words elicited an enhanced late going desynchronization of theta-band power (723-938 ms post stimulus onset) during associate generation. During mental imagery, abstract items elicited greater delta-band power from 800 to 1,000 ms following stimulus onset, theta-band power from 350 to 205 ms before response, and alpha-band power from 900 to 800 ms before response. Overall, the findings support DCT in suggesting that lexical concepts are not amodal and that concreteness effects are modulated by tasks that focus participants on verbal versus nonverbal, imagery-based knowledge.

Prediction-Based Learning and Processing of Event Knowledge.

Knowledge of common events is central to many aspects of cognition. Intuitively, it seems as though events are linear chains of the activities of which they are comprised. In line with this intuition, a number of theories of the temporal structure of event knowledge have posited mental representations (data structures) consisting of linear chains of activities. Competing theories focus on the hierarchical nature of event knowledge, with representations comprising ordered scenes, and chains of activities within those scenes. We present evidence that the temporal structure of events typically is not well-defined, but it is much richer and more variable both within and across events than has usually been assumed. We also present evidence that prediction-based neural network models can learn these rich and variable event structures and produce behaviors that reflect human performance. We conclude that knowledge of the temporal structure of events in the human mind emerges as a consequence of prediction-based learning.

A model of event knowledge.

Our knowledge of events and situations in the world plays a critical role in our ability to understand what is happening around us, to predict what might happen next, and to comprehend language. What has not been so clear is the form and structure of this knowledge, how it is learned, and how it is deployed in real time. Despite many important theoretical proposals, often using different terminology such as schemas, scripts, frames, and event knowledge, developing a model that addresses these three questions (the form, learning, and use of such knowledge) has remained an elusive challenge for decades. In this article, we present a connectionist model of event knowledge that attempts to fill this gap. From sequences of activities, the model learns both the internal structure of activities as well as the temporal structure that organizes activity sequences. The model simulates a wide range of human behaviors that have been argued to involve the use of event knowledge and the temporal structure of events. Furthermore, it makes testable predictions about behaviors not yet observed. Most importantly, the model's ability to learn event structure from experience is a novel solution to the question, "What is the form and representation of event knowledge?" (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Late positive complex in event-related potentials tracks memory signals when they are decision relevant.

The Late Positive Complex (LPC) is an Event-Related Potential (ERP) consistently observed in recognition-memory paradigms. In the present study, we investigated whether the LPC tracks the strength of multiple types of memory signals, and whether it does so in a decision dependent manner. For this purpose, we employed judgements of cumulative lifetime exposure to object concepts, and judgements of cumulative recent exposure (i.e., frequency judgements) in a study-test paradigm. A comparison of ERP signatures in relation to degree of prior exposure across the two memory tasks and the study phase revealed that the LPC tracks both types of memory signals, but only when they are relevant to the decision at hand. Another ERP component previously implicated in recognition memory, the FN400, showed a distinct pattern of activity across conditions that differed from the LPC; it tracked only recent exposure in a decision-dependent manner. Another similar ERP component typically linked to conceptual processing in past work, the N400, was sensitive to degree of recent and lifetime exposure, but it did not track them in a decision dependent manner. Finally, source localization analyses pointed to a potential source of the LPC in left ventral lateral parietal cortex, which also showed the decision-dependent effect. The current findings highlight the role of decision making in ERP markers of prior exposure in tasks other than those typically used in studies of recognition memory, and provides an initial link between the LPC and the previously suggested role of ventral lateral parietal cortex in memory judgements.

Synthesis and cannabinoid activity of 1-substituted-indole-3-oxadiazole derivatives: novel agonists for the CB1 receptor.

An exploratory chemical effort has been undertaken to develop a novel series of compounds as selective CB(1) agonists. It is hoped that compounds of this type will have clinical utility in pain control, and cerebral ischaemia following stroke or traumatic head injury. We report here medicinal chemistry studies directed towards the investigation of a series of 1-substituted-indole-3-oxadiazoles as potential CB(1) agonists.

Abstract Concepts and Pictures of Real-World Situations Activate One Another.

concepts typically are defined in terms of lacking physical or perceptual referents. We argue instead that they are not devoid of perceptual information because knowledge of real-world situations is an important component of learning and using many abstract concepts. Although the relationship between perceptual information and abstract concepts is less straightforward than for concrete concepts, situation-based perceptual knowledge is part of many abstract concepts. In Experiment 1, participants made lexical decisions to abstract words that were preceded by related and unrelated pictures of situations. For example, share was preceded by a picture of two girls sharing a cob of corn. When pictures were presented for 500 ms, latencies did not differ. However, when pictures were presented for 1,000 ms, decision latencies were significantly shorter for abstract words preceded by related versus unrelated pictures. Because the abstract concepts corresponded to the pictured situation as a whole, rather than a single concrete object or entity, the necessary relational processing takes time. In Experiment 2, on each trial, an abstract word was presented for 250 ms, immediately followed by a picture. Participants indicated whether or not the picture showed a normal situation. Decision latencies were significantly shorter for pictures preceded by related versus unrelated abstract words. Our experiments provide evidence that knowledge of events and situations is important for learning and using at least some types of abstract concepts. That is, abstract concepts are grounded in situations, but in a more complex manner than for concrete concepts. Although people's understanding of abstract concepts certainly includes knowledge gained from language describing situations and events for which those concepts are relevant, sensory and motor information experienced during real-life events is important as well.

A common neural substrate for perceiving and knowing about color.

Functional neuroimaging research has demonstrated that retrieving information about object-associated colors activates the left fusiform gyrus in posterior temporal cortex. Although regions near the fusiform have previously been implicated in color perception, it remains unclear whether color knowledge retrieval actually activates the color perception system. Evidence to this effect would be particularly strong if color perception cortex was activated by color knowledge retrieval triggered strictly with linguistic stimuli. To address this question, subjects performed two tasks while undergoing fMRI. First, subjects performed a property verification task using only words to assess conceptual knowledge. On each trial, subjects verified whether a named color or motor property was true of a named object (e.g., TAXI-yellow, HAIR-combed). Next, subjects performed a color perception task. A region of the left fusiform gyrus that was highly responsive during color perception also showed greater activity for retrieving color than motor property knowledge. These data provide the first evidence for a direct overlap in the neural bases of color perception and stored information about object-associated color, and they significantly add to accumulating evidence that conceptual knowledge is grounded in the brain's modality-specific systems.

Verb aspect and the activation of event knowledge.

The authors show that verb aspect influences the activation of event knowledge with 4 novel results. First, common locations of events (e.g., arena) are primed following verbs with imperfective aspect (e.g., was skating) but not verbs with perfect aspect (e.g., had skated). Second, people generate more locative prepositional phrases as completions to sentence fragments with imperfective than those with perfect aspect. Third, the amplitude of the N400 component to location nouns varies as a function of aspect and typicality, being smallest for imperfective sentences with highly expected locations and largest for imperfective sentences with less expected locations. Fourth, the amplitude of a sustained frontal negativity spanning prepositional phrases is larger following perfect than following imperfective aspect. Taken together, these findings suggest a dynamic interplay between event knowledge and the linguistic stream.